MINNEAPOLIS, MN, U.S.A. --- (METERING.COM) --- May 23, 2008 - The Ecologic Integration Lab has been opened by meter data management systems (MDMS) and solutions and decision management technologies provider Ecologic Analytics (formerly WACS).
Furthermore the company has completed integration of its MDMS with the STAR® Network system version 7.0 for electric meters from Aclara (formerly Hexagram) and with Landis+Gyr’s (formerly Cellnet+Hunt) UtiliNet Solution Center system version 2.1. These are added to the 13 existing integration gateways in use by nearly 11 million meters managed with the Ecologic MDMS in production at various clients.
The Ecologic Integration Lab is a comprehensive testing platform and environment that scales to match its partners’ testing environments. The lab allows Ecologic Analytics and participating partners to interactively collaborate to create interfaces and services that allow seamless integration while performing thorough testing to ensure Advanced Meter Infrastructure (AMI) interfaces are ready for production environments of utility clients.
According to research by Datamonitor, the percentage of North American households with a smart meter will grow from six percent today to 89 percent by 2012. The expansion of AMI meter deployments will bring about rapid changes in how meter data is provisioned, stored and used, which will force utilities to adopt strategies to quickly take advantage of the AMI data.
“In addition to the rapid pace of change, utilities are deploying multiple types of AMI technologies simultaneously to provide quality electric, natural gas and water services to diverse service territories,” says David Hubbard, co-founder and chief technology officer for Ecologic Analytics. “Our goal is to put our customers in a position to work seamlessly with any AMI solution provider, now and as their business needs change and grow.”
The integration protocols and interfaces tested in the lab are analyzed to ensure proper bidirectional data flow between the utility and the AMI technology systems and that anomalous situations are handled according to a customer’s specification. Such testing prior to deployment reduces risk, shortens implementation timelines and takes advantage of new AMI features as they become available.